Bibliographic record
Abstract
OBJECTIVE: Identify independent clinical and audiometric factors to predict a positive high-resolution computed tomography (HRCT) scan for superior canal dehiscence (SCD). STUDY DESIGN: Retrospective chart review. SETTING: Tertiary referral center. PATIENTS: Patients presenting SCD. INTERVENTION(S): Audiogram, VEMP, temporal bone HRCT, and SCD symptoms and signs chart. MAIN OUTCOME MEASURE(S): ABG, VEMP threshold, and symptoms and signs. RESULTS: Approximately 106 patients with SCD symptoms were included: 62 had a positive and 44 had a negative CT scan. The positive scan group showed a higher average of cochlear symptoms than the negative CT scan group (4.3 versus 2.6) (p < 0.001), but no statistical difference for vestibular symptoms (2.2 versus 1.8) was identified. CVEMP thresholds of the positive and negative CT scan groups were of 66 and 81 dB, respectively (p < 0.001). The positive CT scan group showed higher ABGs at 250 Hz (24 versus 14 dB) and 500 Hz (17 versus 8 dB) (p = 0.008 and p = 0.008, resectively). No statistical significance was found when comparing both groups for air and bone conduction thresholds. Approximately 23% of the positive CT scan group showed a Valsalva-induced vertigo against 2.3% of the negative scan group (p = 0.003); 27% of the positive CT scan group showed speculum-induced vertigo but none of the negative scan patients (p < 0.001). Using logistic regression, we found that each 10-dB unit increase in the 250 Hz ABG is associated to an increase odd of having SCD of 51% (OR, 1.51; 95% CI, 1.10-2.08). CONCLUSION: Nature and number of cochlear symptoms, Valsalva and pneumatic speculum-induced vertigo, VEMP thresholds, and ABGs seem to correlate with a positive HRCT. The ABG at 250 Hz is the most accurate predictor of SCD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".